论文标题
命中无记忆可可的光子储层计算体系结构
Hitless memory-reconfigurable photonic reservoir computing architecture
论文作者
论文摘要
储层计算是一种模拟生物启发的计算模型,用于有效处理时间依赖性信号,其光子实现有望结合大量并行信息处理,低功耗和高速操作。但是,大多数实现,尤其是对于时间延迟储层计算(TDRC)的情况,需要在储层中信号衰减,以实现特定任务的所需系统动力学,通常会导致大量功率在系统之外耦合。我们提出了一种基于集成在谐振腔中的不对称的Mach-Zehnder干涉仪(MZI)的新型TDRC架构,该干涉仪(MZI)允许对系统的存储能力进行调整,而无需光学衰减器块。此外,可以利用这是为了找到总内存能力度量的特定组件的最佳值。我们在时间上的XOR任务上证明了这种方法,并得出结论,这种内存能力重新配置的方式可以实现特定于内存的任务的最佳性能。
Reservoir computing is an analog bio-inspired computation model for efficiently processing time-dependent signals, the photonic implementations of which promise a combination of massive parallel information processing, low power consumption, and high speed operation. However, most implementations, especially for the case of time-delay reservoir computing (TDRC), require signal attenuation in the reservoir to achieve the desired system dynamics for a specific task, often resulting in large amounts of power being coupled outside of the system. We propose a novel TDRC architecture based on an asymmetric Mach-Zehnder interferometer (MZI) integrated in a resonant cavity which allows the memory capacity of the system to be tuned without the need for an optical attenuator block. Furthermore, this can be leveraged to find the optimal value for the specific components of the total memory capacity metric. We demonstrate this approach on the temporal bitwise XOR task and conclude that this way of memory capacity reconfiguration allows optimal performance to be achieved for memory-specific tasks.